ANALYZING WEB SITES USING ARTIFICIAL INTELLIGENCE

Tuychiyev Khurshidbek Mukhamatvali ugli

Authors

Tuychiyev Khurshidbek Mukhamatvali ugli Assistant Professor, Department of "Modern Information and Communication Technologies", International Islamic Academy of Uzbekistan

Keywords:

AI-powered web analysis, Website performance optimization, User behavior analysis, SEO automation, Content categorization, Sentiment analysis, Personalized recommendations, Website accessibility, AI in cybersecurity, Web analytics tools, User experience (UX) optimization, Machine learning in web design, A/B testing with AI, Website engagement analysis, Real-time data analysis, Dynamic website optimization

Abstract

The use of Artificial Intelligence (AI) in website analysis represents a significant leap in understanding and optimizing online performance. AI-driven analytics tools provide businesses with powerful methods to evaluate and enhance various aspects of a website, including site performance, user experience, content, and functionality. These methods help organizations derive valuable insights into user behavior, preferences, and patterns, which are essential for improving engagement and boosting conversions.
At the heart of AI-powered website analytics is Machine Learning (ML), a subset of AI that allows algorithms to analyze large datasets, recognize patterns, and make predictions based on historical data. By utilizing ML, AI tools can track and analyze user actions, segment audiences, and predict customer behaviors with greater accuracy. This process is particularly useful in Predictive Modeling, where AI analyzes past user interactions to identify correlations between factors such as time, demographics, browsing habits, and conversion rates.